pandas 自定义函数操作 排序 Serials层级索引，层级索引转DF对象，DF对象转置

pandas 自定义函数操作

df1=pd.DataFrame(np.random.randint(-10,10,(4,5)),columns=list('abcde'))
print(df1)
print()
def func(x):

    num=np.max(x)-np.min(x)
    return num
按行列进行自定义运算
app1=df1.apply(func,axis=0)
print(app1)
print()
print(df1.apply(lambda  x:np.max(x)-np.min(x),axis=1))
print()
print(df1.apply(lambda x:x**2,axis=1))
print()
print(df1.apply(lambda x:x*x,axis=1))
print()
print('######################')
def func1(x):

    return abs(x)
每个元素都进行运算
print(df1.applymap(func1))
print()
print(df1.applymap(lambda x:abs(x)))
print()

排序

ser1=pd.Series(np.random.randint(-10,10,10))
df1=pd.DataFrame(np.random.randint(-10,10,(4,5)),index=[2,1,3,5],columns=list('abcde'))
print(ser1)
print(df1)
print('##############')
print()
索引按升序排列
print(ser1.sort_index())
print()
索引按降序排列
print(ser1.sort_index(ascending=False))
print()
print('###############')
值为升序排列
print(ser1.sort_values())
print()
值为降序排列
print(ser1.sort_values(ascending=False))
print()
按'a'列索引排列行
print(df1.sort_values(by='a'))
print()

Serials层级索引，层级索引转DF对象，DF对象转置

df1=pd.DataFrame(np.random.randint(-10,10,(4,5)),index=[2,1,3,5],columns=list('abcde'))
创建多层索引
ser1=pd.Series(np.random.randint(-10,10,10),index=[list('aabbccddee'),[1,2,1,2,1,2,1,2,1,2]])
print(ser1)
print()
print(ser1.index)
print()
print(ser1['a'])
print()
print(type(ser1['a']))
print()
print(ser1['a',1])
print()
print(ser1[:,1])
print()
print(ser1['c',2])
print('##################')
交换层级
print(ser1.swaplevel())
print()
转DF对象
print(ser1.unstack())
print('####################')
DF转层级索引Series对象
print(df1.stack())
print()
print(df1)
print()
DF转置
print(df1.T)
print()
DF变成字典
print(df1.to_dict())
print()
DF转CSV格式
print(df1.to_csv())